On the surface, AWS resource tags are simple, informational key:value metadata that you can assign to most AWS resources. They also have many hidden benefits, as outlined in this AWS Tagging Best Practices guide for improving cloud operations. There are six use cases author Brian Yost calls out in particular:
- AWS console organization and resource groups
- Operations support
- Cost allocation
- Access control
- Security risk management
In summary, tags can simplify operational processes, improve security posture, speed up mean time to resolution (MTTR) and even save money if implemented consistently and persistently. But, unfortunately, in large organizations, that’s a tedious and often faulty process.
To help teams overcome that challenge and make the most of cloud resource tags, Bridgecrew (recently acquired by Palo Alto Networks) recently launched a new open source tool, Yor. Yor is designed to automatically add consistent, helpful tags to infrastructure-as-code (IaC) templates starting with Terraform, CloudFormation and Serverless Framework. If run locally or added to a continuous integration (CI) pipeline, Yor will add tags like git organization and repository, unique trace ID and commit modifier details to IaC resources that carry through to cloud resources. For example, with Yor, you can tag your aws_instance code block in Terraform, and those tags will show up in your running EC2 instances.
This post will explore how to leverage Yor to achieve the six tagging use cases outlined in the AWS Tagging Best Practices guide.
AWS Console Organization and Resource Groups
Using tags to organize and filter resources is the simplest and most common use case for tags. If you add tags to resources, such as EC2 instances or database resources, you can filter based on those tags.
If your AWS account has thousands or tens of thousands of resources in a region, filtering is necessary to manage those resources. For example, if you have hundreds of web servers, filter by the git_repo tag Yor added to quickly filter down to the web server(s) for your application.
In that same vein, you can set up resource groups to organize multiple resources across AWS services based on tags. For example, if you want to hunt down the VPC, EC2, internet gateway or database created by your Terraform repository, use Yor’s git_repo tag to group together multiple resources into a single resource group.
Yor excels at simplifying and speeding up operations support. In the words of Brian Yost, “For example, Level 1 support teams could use tags to direct workflow and perform business service mapping as part of the triage process when a monitoring system triggers an alarm.” Yor automatically tags resources with the git organization and modifiers of the cloud resource. This makes it easier to identify the right team and user to patch issues.
If you work in a GitOps organization, this is even more critical. Following GitOps best practices means all changes should be performed in the IaC template, not directly on the cloud resource. So if your security team identifies an open port 22 in runtime using policy-as-code or CSPM tools, such as Bridgecrew, Yor’s tags will make finding the owner of the IaC template easier and faster, lowering MTTR.
Yor takes this a step further. By adding the repository, file and trace tags, Yor helps teams identify not only the code owner but also the exact file and resource block that created that resource misconfiguration.
Large companies often have different profit and loss (P&L) statements for each of their business units. At the end of a reporting period, such as a fiscal quarter, finance teams allocate the expenditures made across the company to the various cost centers.
For traditional IT teams, this usually involves very broad, general estimates. For example, if two organizations share a server rack, you could allocate costs based on virtual CPU time or disk space. Once that scales into dozens of organizations and ephemeral workloads, that allocation is much more difficult. Cloud costs can be just as difficult to allocate. If you have thousands of resources across types (virtual machines, serverless, managed Kubernetes workloads, managed databases, streams, CDNs, etc.) with differing life cycles and life spans, tying those resource costs back to a cost center is difficult.
Cloud tagging simplifies that process. Assuming each team has a git organization, Yor will automatically tag resources with the git_org or custom tags can group git_modifiers into cost center tags, and AWS Cost Explorer will let you filter by those tags to easily allocate costs. You can also export those costs by tag(s) to a CSV file for import into other tools for analysis.
Yor applies those tags reliably and consistently so that finance teams don’t need to dig through different organization name versions, such as combining dev_team_one and devTeam1, or manually categorizing untagged resources.
AWS identity and access management (IAM) policies support the ability to limit control of resources using tags. This simplifies dividing up resources by teams using complex IAM rules.
For example, if you want developers to access only the EC2 instances they provisioned, you can use the git_modifiers tag added by Yor. Yor will automatically tag resources with the git users who edited the IaC code. Then, Yor will add an AWS IAM policy to limit access based on that tag. You’ll also want to add a policy to deny actions such as ec2:CreateTags and ec2:DeleteTags so users can’t just add themselves to other resources.
This is where Checkov, an open source policy-as-code tool, can be leveraged for additional control. Yor can enrich the context for Checkov’s checks, enabling finer-grained policy control. For example, Yor will populate the user identification of whoever modified an IaC template, and Checkov can make sure that only approved team members modified the code. The following is an example of a custom check to determine that only security personnel modified CloudTrail settings.
If the git_modifier tag added by Yor is anything other than “Nimrod,” “Rotem,” or “Naor,” Checkov will show a failed policy check for that custom check for that resource.
By leveraging tags in combination with other tools, such as Lambda functions and backup plans, you can apply automation to specific resources, such as targeting resources for archive, update or deletion.
The AWS Tagging Best Practices guide uses as an example a situation where development resources are turned off during non-business hours. AWS recently released a tool called Instance Scheduler for just such a use case. It is a CloudFormation stack with a Lambda function and DynamoDB instance that automatically starts and stops EC2 and RDS instances based on a pre-defined schedule.
Instance Scheduler takes a tag with a key:value pair; for example, “Schedule” (or a custom key) as the key and the schedule as the value. The schedules can be either one of the preconfigured schedules in the DynamoDB table, like office-hours, or a custom one.
Using simple custom tags in Yor, you can tag every resource in a repository with a schedule by using environment variables such as adding the following to the Yor GitHub Action YAML file:
This results in tags being added to every resource in that IaC directory. With the seattle-office-hours tag, Instance Scheduler will turn off EC2 instances at 5:00 pm Pacific Time and on again at 9:00 am Pacific Time Monday through Friday. This saves money by stopping instances automatically during downtime.
Another popular automation use case is for backups and archival plans. AWS can automatically apply different backup plans based on the tags applied to resources, such as storage and database resources. For example, if certain organizations, such as those that process financial data, need things archived forever, but others only need one year of backup, applying backup plans can move the short-term storage to cheaper options, such as Glacier, and eventually delete them on a schedule.
Security Risk Management
The final use case is risk management. The risk level of cloud resources differs based on whether they are in test or production environments and the sensitivity of the data those resources process and hold. This is another area where you can use simple tags like git_repo to filter down to repositories for applications that deal with sensitive data. You can also leverage complex custom tags. For example, EC2 instances attached to databases with “customer” in the name will get a data_level:sensitive tag.
IT service management tools can apply higher priority to patching and updating resources with tags denoting sensitive data. This is another area where you can leverage Checkov’s graph-based checks in combination with Yor tags to assign higher severity levels to policy violations for resources with sensitive data tags or production environment tags. Assigning priority helps to focus developer attention and mitigate risk faster.
These six tagging use cases are just a few examples of how you can leverage tags to be more efficient and improve your cloud security posture in AWS. The power of Yor’s tracing capabilities enables development and operations teams to work together without requiring complex triage to find the right person and IaC templates. With Yor’s extensibility and custom tagging capabilities, we can’t wait to see what other use cases the community comes up with!